Jan Ciesko

19 papers A 2C 1Journal 4Unranked 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Maya Taylor, Carl Pearson, Luc Berger-Vergiat, Giovanni Long, Jan Ciesko
2025 conf
SC Workshops
Ian Henriksen, Jan Ciesko, Stephen L. Olivier
2024 conf
CLUSTER Workshops
C. Nicole Avans, Jan Ciesko, Carl Pearson, Evan Drake Suggs, Stephen L. Olivier, Anthony Skjellum
2023 conf
CLUSTER Workshops
Daniel Mishler, Jan Ciesko, Stephen Olivier, George Bosilca
2023 conf
IWOMP
Rahulkumar Gayatri, Stephen L. Olivier, Christian R. Trott, Johannes Doerfert, Jan Ciesko, Damien Lebrun-Grandié
2023 C conf
EuroMPI
Evan Drake Suggs, Stephen Olivier, Jan Ciesko, Anthony Skjellum
2022 conf
IWOMP
Jan Ciesko, Stephen L. Olivier
2022 J jnl
IEEE Trans. Parallel Distributed Syst.
Christian R. Trott, Damien Lebrun-Grandié, Daniel Arndt, Jan Ciesko, Vinh Q. Dang, Nathan D. Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy S. Hollman, Dan Ibanez, Nevin Liber, Jonathan R. Madsen, Jeff Miles, David Poliakoff, Amy Powell, Sivasankaran Rajamanickam, Mikael Simberg, Dan Sunderland, Bruno Turcksin, Jeremiah J. Wilke
2020 J jnl
J. Parallel Distributed Comput.
Jan Ciesko, Pedro J. Martínez-Ferrer, Raúl Peñacoba Veigas, Xavier Teruel, Vicenç Beltran
2020 conf
ExaMPI@SC
Noah Evans, Jan Ciesko, Stephen L. Olivier, Howard Pritchard, Shintaro Iwasaki, Ken Raffenetti, Pavan Balaji
2020 A conf
ICS
Vladimir Dimic, Miquel Moretó, Marc Casas, Jan Ciesko, Mateo Valero
2020 conf
EduHPC@SC
Jan Ciesko, David Poliakoff, Daisy S. Hollman, Christian C. Trott, Damien Lebrun-Grandié
2019 J jnl
CoRR
Jan Ciesko, Pedro J. Martínez-Ferrer, Raúl Peñacoba Veigas, Xavier Teruel, Vicenç Beltran
2017
Jan Ciesko
2016 conf
IWOMP
Jan Ciesko, Sergi Mateo, Xavier Teruel, Xavier Martorell, Eduard Ayguadé, Jesús Labarta
2015 conf
HPEC
Jan Ciesko, Sergi Mateo, Xavier Teruel, Vicenç Beltran, Xavier Martorell, Jesús Labarta
2015 conf
IWOMP
Jan Ciesko, Sergi Mateo, Xavier Teruel, Xavier Martorell, Eduard Ayguadé, Jesús Labarta, Alex Duran, Bronis R. de Supinski, Stephen Olivier, Kelvin Li, Alexandre E. Eichenberger
2014 conf
IWOMP
Jan Ciesko, Sergi Mateo, Xavier Teruel, Vicenç Beltran, Xavier Martorell, Rosa M. Badia, Eduard Ayguadé, Jesús Labarta
2013 A conf
IPDPS
Jan Ciesko, Javier Bueno, Nikola Puzovic, Alex Ramírez, Rosa M. Badia, Jesús Labarta
redb/extractors/decompiler/bninja/similarity/minhasher.py
← Index redb/extractors/decompiler/bninja/similarity/minhasher.py python
import logging
import random
from enum import Enum

from ..analysis.medium_level_normalization import MediumLevelNormalization

try:
    from .minhashcustom import MinHashCustom
    from ..analysis.low_level_normalization import LowLevelNormalization
except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.similarity.minhashcustom import MinHashCustom
    from redb.extractors.decompiler.bninja.analysis.low_level_normalization import LowLevelNormalization

## Values for this configuration were extracted from https://github.com/danielplohmann/mcrit/blob/main/mcrit/config/MinHashConfig.py#L10
# Length in number of Shingles of which a minhash consists
# this value represents the length of sha256sum hash truncated
MINHASH_SIGNATURE_LENGTH: int = 64
# Number of bits per signature element (1-32 bits)
MINHASH_SIGNATURE_BITS: int = 8


class TokenKind(Enum):
    LLIL = "llil"
    TYPED_LLIL = "typed_llil"
    MLIL = "mlil"
    TYPED_MLIL = "typed_mlil"


class MinHasher:
    # stick to the default method
    MINHASH_STRATEGY_HASH_ALL = 1

    def __init__(self, seed, il_function, kind: TokenKind = TokenKind.LLIL):
        self._minhash_seeds = []
        self.il_func = il_function
        self.kind = kind
        self._minhash_permutation = []
        self._signature_segments = []
        self._initMinhashing(seed)

    def _initMinhashing(self, MINHASH_SEED=None):
        random.seed(MINHASH_SEED)
        # init sequence of seeds
        self._minhash_seeds = [
            random.randint(0, MinHashCustom.getHashMax()) for _ in range(MINHASH_SIGNATURE_LENGTH)
        ]

    def make_ngrams(self, tokens, n=3):
        """Take the ngrams of the IL we try to pass into the functions"""
        return [tuple(tokens[i:i+n]) for i in range(len(tokens) - n + 1)]

    def _extract_tokens(self):
        """Extract the IL tokens from the IL function, picking the right
        normalizer (LLIL/MLIL) and the right normalization mode
        (skeleton/typed) based on self.kind."""
        if self.kind in (TokenKind.LLIL, TokenKind.TYPED_LLIL):
            normalizer = LowLevelNormalization()
        elif self.kind in (TokenKind.MLIL, TokenKind.TYPED_MLIL):
            normalizer = MediumLevelNormalization()
        else:
            raise ValueError(f"Unsupported token kind: {self.kind}")

        # typed variants include operand type info, skeleton variants don't
        if self.kind in (TokenKind.TYPED_LLIL, TokenKind.TYPED_MLIL):
            normalize = normalizer.normalize_instr_with_operands
        else:
            normalize = normalizer.normalize_instruction_all_levels

        instructions = []
        for basic_block in self.il_func.basic_blocks:
            for il in basic_block:
                instructions.append(normalize(il))

        return instructions

    def calculateMinHash(self):
        """Calculate hash function every time, then take minimum shingle per shingler"""
        minhash_result = MinHashCustom(minhash_bits=MINHASH_SIGNATURE_BITS)
        minhash_signature = []

        tokens = self._extract_tokens()
        shingles = self.make_ngrams(tokens, n=3)

        # Functions with fewer than 3 IL instructions can't produce n-grams
        # Return empty minhash for such small functions (thunks, stubs, etc.)
        # Triggered by 39d8ad95b0323c37bd3134ab93ac4af44c66a1a8443a41c1ac02cec19bb2816a
        if not shingles:
            return []

        # Generate the MinHash
        for seed in self._minhash_seeds:
            hashed_shingles = [
                self.shingle_hash(shingle, seed) for shingle in shingles
            ]
            min_value = min(hashed_shingles)

            if MINHASH_SIGNATURE_BITS < 32:
                min_value %= (2 ** MINHASH_SIGNATURE_BITS)

            minhash_signature.append(min_value)

        minhash_result.setMinHash(minhash_signature)
        return minhash_result.getMinHashInt()

    def shingle_hash(self, shingle, hash_seed=0):
        """Produce a single 32bit UINT hash for a given shingle"""
        return MinHashCustom.hashData(shingle, hash_seed)